ray.rllib.algorithms.algorithm.Algorithm.restore_workers

Algorithm.restore_workers(workers: WorkerSet) → None

Try bringing back unhealthy EnvRunners and - if successful - sync with local.

Algorithms that use custom EnvRunners may override this method to disable the default, and create custom restoration logics. Note that “restoring” does not include the actual restarting process, but merely what should happen after such a restart of a (previously failed) worker.

Parameters:

workers – The WorkerSet to restore. This may be the training or the evaluation WorkerSet.